"Ideal" Language Learning and the Psychological Resource Problem

10/19/2007 3:50 Wong AuditoriumWilliam Gregory Sakas, Associate Professor, Department of Computer Science, Hunter College; Ph.D. Programs in Computer Science and Linguistics, The Graduate Center, City University of New York

Description: Some linguists study what can be learned in principle, but William Gregory Sakas asks "the feasibility question -- how efficient learning takes place." This talk focuses on such research, its historical antecedents, and issues that trouble Sakas and his colleagues.

Sakas provides a swift conceptual survey of modeling parameter"setting, from Chomsky, through Yang and Lightfoot. In "the spirit of Pinker," Sakas believes that any computational model of a feasible learner must be compatible with the psychological resources of a human child. So Sakas's lab tries to zero in on "what is needed in the way of psycho"computational resources in a learner to converge on the target grammar on the basis of a limited sample of sentences." The lab has created "a large, artificial but linguistically motivated domain of parameterized languages for evaluating learning models," with more than 1.6 million parsed sentences. Sakas and his colleagues compare the efficiencies of different parameter"setting models, attempt to solve such modeling problems as noise and over"generalization, as well as evaluate richness of the stimulus claims.

Underlying this work _ "the whole parameter setting enterprise" -- says Sakas, is the effort "to limit the resources to what can reasonably be attributed to young children," so as to reduce the complexity of innate knowledge -- generally limit the amount and complexity of input and processing of each sentence. The sticky problem remains of finding a "psycho"computationally palatable way" of modeling a process of fitting grammar to multiple sentences.

"We feel alone in this endeavor," says Sakas. While there's lots of interesting recent work on modeling syntax acquisition, mathematical, and statistical/probabilistic learning, "we haven't been able to take it into our models, because it doesn't seem to be concerned with resource limits." The ideal learner other linguists discuss "is not a learner concerned with resource issues." Sakas asks if "this work is intended to mirror psychological reality." He notes, "The effective richness of the stimulus for a child language learner depends on the child's non"ideal capacity to extract information from heard utterances." The point is to model what a child really does with the linguistic input available to her. Sakas concludes with a question: "Is there anyone out there trying to solve the psychological resource problem?

About the Speaker(s): William Gregory Sakas has been a professor at CUNY/Hunter College since September 2000.

He has published a book chapter with J.D. Fodor in Language Acquisition and Learnabilityand co"authored a textbook, The Core Guide to PPL Programming.

He received his A.B. from Harvard College in Economics and his Ph.D. in Computer Science from the City University of New York.

Host(s): School of Engineering, Laboratory for Information and Decision Systems